Emerging TechnologyFive examples that demonstrate the value of AI for B2B marketers

Five examples that demonstrate the value of AI for B2B marketers

Five examples of AI’s use in B2B marketing technologies including ABM platforms, predictive analytics, AI-powered CRMs, and predictive compliance for social media campaigns.

30-second summary:

  • The global AI software market is expected to reach nearly $23 billion by 2025, according to data from Statista.
  • AI offers several powerful functionalities within in ABM platforms to facilitate selling.
  • Predictive analytics, which uses historical data, machine learning, and statistical algorithms to predict future outcomes, it’s particularly useful for campaign planning and optimization.
  • CRM tools like HubSpot and Salesforce Einstein have AI features like predictive analytics and machine learning built in.
  • AI can help brands in heavily regulated industries avoid compliance issues when posting to social media via the use of AI.
  • DAM platforms enhanced with AI capabilities help to streamline and automate many aspects of managing distributed content such as images, video, and other media.

If it seems like AI is everywhere these days, that’s probably because it is. The global AI software market is expected to reach nearly $23 billion by 2025, according to data from Statista.

AI has implications for every industry, but it’s particularly ubiquitous in marketing, with numerous applications and solutions covering a range of capabilities from content management to team collaboration to account-based marketing.

The Chiefmartec Supergraphic, once called the Martech 5000, has officially been dubbed the Marketing Technology Landscape (as of April 2020). The updated graphic attempts to map more than 8000 companies across six marketing categories and does, in fact, look like the map of a strange new world.

Chiefmartec’s Marketing Technology Landscape — April 2020

With so many different martech tools and platforms available, it can be difficult to figure out what solution is worth your time and money.

While not every solution has AI capabilities, many of them have some type of AI/machine learning element to them, making it difficult to know which tools can truly make your organization more efficient while contributing to your company’s overall growth.

Example #1: AI-powered account-based marketing platforms

Account-based marketing (ABM) platforms like Demandbase and Terminus enable B2B marketing and sales teams to target companies that align well with their existing clients.

An ABM strategy shifts the focus of your marketing team from generating large volumes of leads to identifying and reaching out to fewer, more qualified prospects.

Platforms like Demandbase facilitate this approach by enabling users to build audiences using their existing CRM, account, and customer data.

AI offers several powerful functionalities within in ABM platforms that range from automating the process of account discovery based on pre-defined criteria to real-time traffic analysis that enables personalization of content for web users (another Demandbase feature).

Example #2: Predictive analytics in the context of marketing

Predictive analytics uses historical data, machine learning, and statistical algorithms to predict future outcomes. There are many different applications and solutions that employ predictive analytics for marketers, but it’s particularly useful for campaign planning and optimization.

For example, Terminus, another top tier ABM platform, announced the addition of machine-learning and predictive analytics capabilities this past October.

These new capabilities help automate processes such as account discovery by sending out emails to sales reps that contain “high-fit” accounts they aren’t already targeting. This saves them time they would have spent sifting through and analyzing the data manually.

Terminus’s technology also enables users to set up automated marketing campaigns using targets that the system surfaces via AI. The platform uses AI to automatically score accounts based on engagements, intent data, and other information.

Marketo, Adobe’s marketing automation platform, is another example of how predictive analytics can help marketers save time and reduce errors. It crawls a user’s website and identifies assets that can be used in marketing campaigns such as videos, e-books, and case studies.

The system predicts the most relevant content to show to individual website visitors and provides AI-powered suggestions which optimizes existing content and identifies the best performing content.

Example #3: AI-powered customer relationship management (CRM)

CRM tools like HubSpot and Salesforce Einstein have AI features like predictive analytics and machine learning built in.

Einstein uses predictive analytics to identify patterns and trends in customer behavior that can help identify leads and opportunities and alert employees about them so they can quickly act on them. It also automates one of the most painful tasks associated with maintaining a CRM system — data entry.

Per Salesforce’s website, Einstein enables users to, “Automatically capture and log critical customer data – including contact info, email threads, calendar events, social data, and more – right into the associated Salesforce records.”

Other AI-driven features available in Einstein include helping to resolve customer issues faster using AI-driven chatbots, streamlining workflows based on predictions and recommendations, and predicting business outcomes such as churn and lifetime value.

HubSpot also has built in AI capabilities including content intelligence which can help users understand the best topics to focus on and predictive lead scoring, which automatically surfaces the best leads by using custom models to score leads in a database.

HubSpot also uses AI to automatically enrich CRM data with details about prospects that can be used for lead scoring.

Example #4: AI-enabled regulatory compliance on social media

Hootsuite, a popular social media management platform that helps users track and manage their social media presence across multiple platforms recently partnered with Proofpoint, an enterprise security company, to help brands in heavily regulated industries avoid compliance issues via the use of AI.

They call the feature “Predictive Compliance” and it uses AI to alert users of compliance policy violations (they must be logged into Hootsuite when composing the social media post for the tool to work).

The alerts occur in real-time as the user is typing. The tool can even be set to hold a post until the error is correcting, saving the user embarrassment and (theoretically) reducing the workload for compliance personnel who no longer must review and monitor social media posts.

So, while Hootsuite does not have the AI-capabilities built in, their partnership with Proofpoint ads this functionality to the platform, enabling marketers to deploy social media campaigns with more confidence.

Solution #5: AI-powered digital asset management (DAM)

A digital asset management (DAM) platform is used by organizations for the purpose of collecting, organizing, managing, and distributing digital assets to employees via one central location.

DAM platforms enhanced with AI capabilities help to streamline and automate many aspects of managing distributed content such as images, video, and other media. Marketing teams benefit when their organizations use a DAM platform because it helps them easily (and quickly) locate digital assets for their campaigns.

For example, an AI-powered DAM can automate the process of tagging images, making them searchable throughout the organization. This is incredibly helpful when you have large amounts of content to organize and tag. DAMs also help with version control, ensuring that only approved assets are utilized in marketing campaigns and on social media.

Bynder is an example of an AI-powered DAM platform with capabilities that include image tagging, organization, and categorization.

The possibilities are endless

This article only scratches the surface of the AI-powered tools available to today’s marketers. AI is everywhere — from chatbots (e.g., conversational AI) to audience segmentation to sales forecasting.

AI has the potential to help marketers be more efficient and effective by eliminating redundant tasks, reducing human error, and streamlining business processes.

You may already be familiar with solutions mentioned above or they may be new to you, but each of them can help you save time, reduce errors, and allow your marketing and sales teams to focus on what they’re best at — growing your business.

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